The present invention relates to a data retrieval apparatus for retrieving desired data from a variety of databases and more particularly, to a data retrieval apparatus capable of performing a data retrieval action at high efficiency according to the subjective criteria or requirements of the user.
Advanced data retrieval methods have been developed for retrieving data in accordance with a personal standard of subjective judgment, e.g. human concepts like proper and convenient. In such data retrieval methods, a retrieval apparatus identifies specific criteria determined by user's requirements and executes a data retrieval action according to the criteria. For example, among them is a fuzzy retrieval system with a fuzzy connective operator depicted in "Construction of Fuzzy Retrieval System with Learning-type Fuzzy Connective Operator", the 1991 Electric and Information Institutes Joint Conference, Literature S4-1. The fuzzy connective operator is defined by Equation (1). Also, S and T in Equation (1) are expressed in Equation (2). ##EQU1##
The fuzzy connective operator of Equation (1) is a variable in the function by changing the values of parameters p1, p2, . . . , pn+3. The values of parameters are determined by a learning process in order to correspond to the subjective criteria. In Equation (1), x is the input data and m is the value determined by the input data x.
FIG. 11 illustrates a block diagram showing a prior art data retrieval apparatus using the fuzzy connective operator. As shown, there are provided a membership function input 101 for receiving membership functions which represent a part of the subjective criteria of a user, a memory 102 for storing the membership functions, a data storage 103 for storing data which consists of quantitative attributes, (e.g. the number of employees and the amount of monthly payment), a membership degree calculator 104 for calculating the degree of membership of each attribute of the data to the membership functions, an assembler 105 for aggregating the degrees of membership of the attributes using the fuzzy connective operator, a retrieval result display 106 for displaying retrieval results which have been selected from the data in response to the output of the assembler 105, a user evaluation input 107 for allowing the user to enter an evaluation value of the subjective criteria when the display indicates that the retrieval output fails to match the subjective criteria of the user, and a controller 108 for modifying the parameters of the fuzzy connective operator with the evaluation value.
The operation of the prior art data retrieval apparatus shown in FIG. 11 will be explained in more detail. Subjective data are entered by the user in the form of membership functions through the membership function input 101 into the data retrieval apparatus and transferred to the memory 102 for temporary storage. For example, when the data retrieval apparatus is designed for selecting a desirable hotel(s) from a database of accommodation facilities, the user who is looking for a business hotel may enter his subjective requirements, (e.g. a preferred distance to a location to be visited and a payable amount for hotel fee,) into the membership function input 101.
Then, the degrees of membership of the attributes of each storage data of the data storage 103 are examined by the membership degree calculator 104 in relation to the membership functions fed from the memory 102. More specifically, the degree of the membership of a data attribute, (e.g. the distance of a hotel to the location or the hotel fee), to the corresponding membership function is calculated. The degrees of membership of the attributes are aggregated in the assembler 105 using the fuzzy connective operator expressed by Equation 1.
Through observing the output of the assembler 105, a data which satisfies the given condition (for example, it is greater than a particular value) is retrieved and displayed on the retrieval result display 106. The retrieval result display 106 also indicates the output of the assembler 105 calculated by the fuzzy connective operator. The user then examined the displayed data and accepts it as a retrieved result when it satisfies the user criteria requirements.
If the displayed data fails to satisfy the user's subjective requirements, the user evaluation data determined personally by the user is entered into the user evaluation input 107. In response to the user evaluation data, a controller 108 changes the parameters (P.sub.1, . . . ,P.sub.n+3) of the fuzzy connective operator shown in Equation (1) to produce a more preferable output suited to the user's requirements. As set forth above, the prior art data retrieval apparatus is capable of changing the parameters of the fuzzy connective operator according to the user evaluation data which has been determined by the user in response to the uncompensated retrieval result. Accordingly, the data retrieval with the fuzzy connective operator can successfully be conducted according to the subjective criteria of the user.
However, in the prior art data retrieval apparatus, two intricate processes, calculation of the degree of membership of stored data to the membership functions entered by the user and aggregation of the degrees of membership using the fuzzy connective operator, have to be executed on all the stored data. As the stored data becomes large, the time required for retrieving them will be increased considerably.
Also, the prior art data retrieval apparatus displays the criteria used in the retrieval procedure in a manner which is not very clear to the user because the criteria are not expressed in the easily understandable form of retrieval conditions, (e.g. an order of size.) It is thus difficult for the user to acknowledge that the user evaluation data is correctly entered and treated by the data retrieval apparatus. Even if some of the retrieval conditions are possibly defined by equality and/or inequality statements, they cannot be entered directly into the data retrieval apparatus but only in the form of membership functions and user evaluation data.